The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Electric vehicle charging demand forecasting model based on big data technologies
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Citations
Cites
Applied Multivariate Statistical Analysis.
Johnson, A. R., & Wichern, D. W. (1988) · Biometrics · doi:10.2307/2531616 · Cited by 11,353
Applied Multivariate Statistical Analysis
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Modeling of Load Demand Due to EV Battery Charging in Distribution Systems
Qian, K., Zhou, C., Allan, M., & Yuan, Y. (2011) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2010.2057456 · Cited by 1,268
An Optimized EV Charging Model Considering TOU Price and SOC Curve
Cao, Y., Tang, S., Li, C., Zhang, P., Tan, Y., Zhang, Z., & Li, J. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2011.2159630 · Cited by 719
Power-based electric vehicle energy consumption model: Model development and validation
Fiori, C., Ahn, K., & Rakha, H. A. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.01.097 · Cited by 641
Spatial and Temporal Model of Electric Vehicle Charging Demand
Bae, S., & Kwasinski, A. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2011.2159278 · Cited by 474
Self-citationA spatial–temporal model for grid impact analysis of plug-in electric vehicles
Mu, Y., Wu, J., Jenkins, N., Jia, H., & Wang, C. (2014) · Applied Energy · doi:10.1016/j.apenergy.2013.10.006 · Cited by 424
Comparison of hierarchical cluster analysis methods by cophenetic correlation
Saraçli, S., Doğan, N., & Doğan, İ. (2013) · Journal of Inequalities and Applications · doi:10.1186/1029-242x-2013-203 · Cited by 354
Stochastic analyses of electric vehicle charging impacts on distribution network
Leou, R.-C., Su, C.-L., & Lu, C.-N. (2014) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2291556 · Cited by 336
A Methodology for Optimization of Power Systems Demand Due to Electric Vehicle Charging Load
Zhang, P., Qian, K., Zhou, C., Stewart, B. G., & Hepburn, D. M. (2012) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2186595 · Cited by 286
Cited by
Big data analytics in supply chain management between 2010 and 2016: Insights to industries
Tiwari, S., Wee, H. M., & Daryanto, Y. (2018) · Computers & Industrial Engineering · doi:10.1016/j.cie.2017.11.017 · Cited by 582
Fault and defect diagnosis of battery for electric vehicles based on big data analysis methods
Zhao, Y., Liu, P., Wang, Z., Zhang, L., & Hong, J. (2017) · Applied Energy · doi:10.1016/j.apenergy.2017.05.139 · Cited by 375
Al-Ogaili, A. S., Tengku Hashim, T. J., Rahmat, N. A., Ramasamy, A. K., Marsadek, M. B., Faisal, M., & Hannan, M. A. (2019) · IEEE Access · doi:10.1109/access.2019.2939595 · Cited by 303
Daily electric vehicle charging load profiles considering demographics of vehicle users
Zhang, J., Yan, J., Liu, Y., Zhang, H., & Lv, G. (2020) · Applied Energy · doi:10.1016/j.apenergy.2020.115063 · Cited by 259
Gonzalez Venegas, F., Petit, M., & Perez, Y. (2021) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2021.111060 · Cited by 244
Metadata
- Authors
- Arias, M. B., & Bae, S.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2016-12
- Volume
- 183
- Pages
- 327-339
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W2507562171
- Cited by
- 346
- References
- 27
- FWCI
- 7.78
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Electric vehicle charging demand forecasting model based on big data technologies. https://app.cochat.ai/papers/10.1016/j.apenergy.2016.08.080
- The paper
- Arias, M. B., & Bae, S. (2016). Electric vehicle charging demand forecasting model based on big data technologies. Applied Energy. https://doi.org/10.1016/j.apenergy.2016.08.080
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
